This section introduces aspects that may help facilitate a better understanding of the disclosure. Accordingly, these statements are to be read in this light and are not to be understood as admissions about what is or is not prior art.
Patch-clamp recording is a gold-standard technique for accurate measurement of membrane voltage fluctuations, synaptic currents and ionic channel activity in neurons. It has allowed neuroscientists to study properties of individual ion channels and synapses and to characterize synaptic plasticity and dendritic integration. Patch-clamp recording has also been essential for dissecting the pathophysiology of neurological disorders caused by mutations in channels and synaptic proteins. In combination with morphological characterization, this method has been used for classifying cell types in the brain and elucidating connectivity among nearby neurons. It has also been successfully coupled with optogenetics and applied to map long-range neuronal circuits.
A typical patch-clamp experiment is highly repetitive, making it strenuous and error-prone for the investigator. Typically, a neuron is first manually located, a micropipette is brought into vicinity of the neuron, and then through incremental one-dimensional movements the micropipette is brought into contact with the neuron by applying a pressure to the neuron's surface. When advancing the micropipette towards the target cell, errors such as advancing the pipette too far into the tissue, breaking the pipette tip, and/or improperly setting the pipette pressure are common among novices and occasional among experienced researchers. Furthermore, these errors usually accumulate toward the end of a day when researchers get tired.
Some steps of the patch-clamp process are difficult to control manually. For example, the delicate pneumatic pressure changes applied to the pipette are necessary to form a whole-cell configuration. This pressure control is typically done by mouth or with syringe, making them difficult to replicate among labs and even among different investigators in the same lab. There is also a plethora of undocumented heuristics, such as the magnitude of pressure, number of pressure pulses, and time to match cell membrane potential (−70 mV), that are challenging to master and vary from lab to lab. This is especially an issue when large datasets collected by various laboratories for a single study must be directly comparable. Further, while the integration of patch-clamp recording with other techniques such as optogenetics is essential for investigating complex circuits in the brain, the additive complexity of the procedure could prohibit new investigators from initiating such projects, despite the high scientific interest and large data set demand.
Prior to the disclosure within the present application, there was no comprehensive solution which automates the patch-clamp procedure in vitro. While fully automated planar patch-clamp systems have been commercially available for years and have been instrumental in high-throughput drug discovery applications, they are only suitable for cells in suspension, but not for neuronal cultures or brain slices. In vivo “blind” patching reported previously was designed to use only electrical resistance, not visual information, as an indicator of cell proximity. However, the electrical resistance measurements are limited to several micrometers of range to successfully detect a neuron. In most of patch-clamp applications targeting cells based on visual cues such as the shape or fluorescence of a cell is required. Prior to the disclosure within the present application, no automation system existed to assist in the performance of such visually-guided patch-clamp experiments in tissue.
There is, therefore an unmet need for an automated patch-clamp system capable of recognizing target cells and identifying location of these cells in order to perform patch-clamp experiments in larger numbers.